Not Just Little Adults: Palliative Care Physician Attitudes Toward Pediatric Patients
Bibliographic record
Abstract
BACKGROUND: Palliative care physicians are increasingly being asked to provide end-of-life (EOL) care for children. Yet very little is known about physicians' level of comfort and willingness to do so. OBJECTIVES: This study assessed the attitudes of palliative care physicians toward providing care for pediatric patients and to describe the supports they desire in order to do so. METHODS: An online questionnaire was e-mailed to all physicians in the Division of Palliative Care at the University of Toronto. The questionnaire explored perceptions, attitudes, and level of comfort caring for pediatric patients. Results are reported using frequencies, ratios, and other descriptive analyses. RESULTS: Forty-four physicians of the 74 (59%) surveyed responded. On average, physicians cared for fewer than one child per each year of practice. Although the majority of respondents perceived their pediatric training to be inadequate, 70% were willing to provide care to children. Respondents felt at ease applying their knowledge and skills in some aspects of pediatric care (e.g., principles of pain and symptom management, communication about EOL issues) but less so in others (e.g., medication dosing, ethical issues unique to pediatrics). All respondents welcomed opportunities for additional training, but a third felt it was not essential. In particular, the most frequently expressed need was for mentorship by pediatric palliative care specialists. CONCLUSIONS: Palliative physicians tend to be willing to care for children, but perceive their level of training to be insufficient. Although additional training is endorsed, physicians favored real-time support and mentorship from a pediatric expert.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".